People Counting in Extremely Dense Crowd using Blob Size Optimization

Estimating Crowd density and counting people is an important factor in crowd management. The increase of number of people in small areas may create problems like physical injury and fatalities. Hence early detection of the crowd can avoid these problems. Counting of the people moving in the crowd can provide information about the blockage at some point or even stampede. In this paper, we have proposed a framework to count people in the extremely dense crowd where people are moving at different speeds. Foreground segmentation is done by various methods of background subtraction namely, approximate median, and frame difference and mixture of Gaussian method. Time complexity is calculated for these techniques and approximate median technique is selected which fast and accurate. Blob analysis is done to count the people in the crowd and blob area is optimized to get the best counting accuracy. Proposed framework is analyzed for three videos from Al-Haram mosque and people counting accuracy is found to be more than 96% in all three videos. [Arif M, Daud S, Basalamah S. People Counting in Extremely Dense Crowd using Blob Size Optimization. Life Sci J 2012;9(3):1663-1673] (ISSN: 1097-8135). http://www.lifesciencesite.com. 242